Translation Invariance in Data Envelopment Analysis

Jesus T. Pastor () and Juan Aparicio
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Jesus T. Pastor: University Miguel Hernandez of Elche

Chapter 8 in Data Envelopment Analysis, 2015, pp 245-268 from Springer

Abstract: Abstract In this chapter we present an overview of the different approaches that have considered translation invariant Data Envelopment Analysis (DEA) models. Translation invariance is a relevant property for dealing with non-positive input and/or non-positive output values. We start by considering the classical approach and continue revising recent contributions. We also consider non-translation invariant DEA models that are able to deal with negative data at the expense of modifying the model itself. Finally, we propose to study translation invariance in a general framework through a recently introduced distance function: the linear loss distance function.

Keywords: Data envelopment analysis; Translation invariance; Negative data; Linear loss distance function (search for similar items in EconPapers)
Date: 2015
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DOI: 10.1007/978-1-4899-7553-9_8

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